The current meta-analysis compared the characteristics of online child pornography-only offenders, typical (offline) sex offenders against children, and offenders with both child pornography and ...contact sex offences against children (mixed). Based on 30 unique samples (comparison
n
s ranging from 98 to 2,702), the meta-analysis found key differences between groups. Offenders who committed contact sex offences were more likely to have access to children than those with only child pornography offences. In contrast, offenders who used the internet to commit sexual offences had greater access to the internet than those with contact sex offenders. Differences between the groups, however, were not limited to differential opportunities. Sex offenders against children and mixed offenders were found to score higher on indicators of antisociality than online child pornography offenders (CPOs). CPOs were also more likely to have psychological barriers to sexual offending than sex offenders against children and mixed offenders (e.g., greater victim empathy). Mixed offenders were found to be the most pedophilic, even more than CPOs. The findings suggest that offenders who restricted their offending behavior to online child pornography offences were different from mixed offenders and offline sex offenders against children, and that mixed offenders were a particularly high risk group.
Objectives: Few studies have examined how much individuals change on intermediate targets of risk to reoffend. Even fewer studies have examined the extent to which change on such measures predict ...reoffending. Establishing the validity of intermediate measures requires a multistep approach that (a) assesses the reliability of the change, (b) assesses change using statistical analyses that can account for measurement error, and (c) examines the extent to which change on these intermediate measures predict reoffending. Method: The current study examined the validity of an intermediate measure of risk to reoffend scored by community supervision officers (i.e., ACUTE-2007) in a large sample of men convicted of sexually motivated offenses (N = 632). Results: We found that risk to reoffend changes across time, the pattern of change varies across individuals, risk levels can predict different patterns of change, and that the best predictors of recidivism are the latest score or a rolling average of scores. Conclusions: Community supervision can use recent information concerning the community adjustment of their clients to predict recidivism. Best practice includes updating assessments and adjusting supervision practices based on their clients' most recent assessment, or the average of previous assessments.
What is the public health significance of this article?
Sexual offending is a serious public health concern. The current article examines how to assess the likelihood of reoffending among men with sexual offenses who are in the community. Our studies suggest that community supervision agents are able to assess changes in the risk for reoffending. Best practice should include reassessments throughout the supervision period and adjusting supervision practices based on the most recent assessment, or an average of the previous assessments.
The pervasiveness of risk assessment in correctional decision-making necessitates a better understanding of the nature of risk scales and the methods used to assess their accuracy. Risk is a ...continuous dimension, which means that risk assessment is a prognostic task as opposed to a diagnostic task. Risk scales can also be considered criterion-referenced as opposed to norm-referenced. Predictive accuracy can be divided into discrimination and calibration. Area under the curves (AUCs), Cox regression, Harrell’s C, Cohen’s d, and logistic regression are appropriate for analyses of discrimination. There is no consensus on calibration statistics, but both chi-square tests and the Expected/Observed (E/O) index have been used and show promise. Statistics intended for dichotomous diagnostic decisions (e.g., positive predictive accuracy and negative predictive accuracy, number needed to detain, number needed to discharge) are inappropriate for risk scales because of the prognostic nature of risk scales. In many circumstances, diagnostic statistics provide more information about the base rate of recidivism than about the risk scale.
Actuarial risk assessment scales and their associated recidivism estimates are generally developed on samples of offenders whose average age is well below 50 years. Criminal behavior of all types ...declines with age; consequently, actuarial scales tend to overestimate recidivism for older offenders. The current study aimed to develop a revised scoring system for two risk assessment tools (Static-99 and Static-2002) that would more accurately describe older offenders’ risk of recidivism. Using data from 8,390 sex offenders derived from 24 separate samples, age was found to add incremental predictive validity to both Static-99 and Static-2002. After creating new age weights, the resulting instruments (Static-99R and Static-2002R) had only slightly higher relative predictive accuracy. The absolute recidivism estimates, however, provided a substantially better fit for older offenders than the recidivism estimates from the original scales. We encourage evaluators to adopt the revised scales with the new age weights.
Correlations are the simplest and most commonly understood effect size statistic in psychology. The purpose of the current paper was to use a large sample of real-world data (109 correlations with ...60,415 participants) to illustrate the base rate dependence of correlations when applied to dichotomous or ordinal data. Specifically, we examined the influence of the base rate on different effect size metrics. Correlations decreased when the dichotomous variable did not have a 50 % base rate. The higher the deviation from a 50 % base rate, the smaller the observed Pearson’s point-biserial and Kendall’s tau correlation coefficients. In contrast, the relationship between base rate deviations and the more commonly proposed alternatives (i.e., polychoric correlation coefficients, AUCs, Pearson/Thorndike adjusted correlations, and Cohen’s
d
) were less remarkable, with AUCs being most robust to attenuation due to base rates. In other words, the base rate makes a marked difference in the magnitude of the correlation. As such, when using dichotomous data, the correlation may be more sensitive to base rates than is optimal for the researcher’s goals. Given the magnitude of the association between the base rate and point-biserial correlations (
r
= −.81) and Kendall’s tau (
r
= −.80), we recommend that AUCs, Pearson/Thorndike adjusted correlations, Cohen’s
d
, or polychoric correlations should be considered as alternate effect size statistics in many contexts.
STABLE-2007 is a measure of risk-relevant propensities for adult males convicted of a sexual offense. This meta-analysis evaluated the ability of STABLE-2007 and its items to discriminate between ...recidivists and nonrecidivists, and the extent to which STABLE-2007 improves prediction over and above Static-99R. Based on 21 studies (12 unique samples, N = 6,955), we found that STABLE-2007 was significantly and incrementally related to sexual recidivism, violent (nonsexual) recidivism, violent (including sexual) recidivism, and any crime. Scores on STABLE-2007 items and the three STABLE-2000 attitude items also discriminated between individuals who sexually reoffended and those who did not sexually reoffend. These findings support the use of STABLE-2007 in applied risk assessment practice and the interpretation of STABLE-2007 items as indicators of treatment and supervision targets.
With the advancement of technology, sexting has become more prominent in high school and university samples. The current study examined the rates and characteristics of sexting among an online sample ...of 2,828 young adults aged 18–30, primarily from the U.S. and Canada. We found that most participants sext (81%), sext often (most report ≥ 11 sexts), and start young (most by 16–17 years of age). Common reasons for sexting echoed reasons for participating in other normative sexual behaviors, including that it was sexually arousing, they were asked and wanted to reciprocate, or they wanted to flirt. Sexual coercion was a gendered phenomenon, with 1 in 10 cisgender women and 1 in 50 cisgender men reporting having sent a sext due to being threatened. The body parts captured in cisgender men’s sexts were more diverse, whereas cisgender women focused on their chest, underwear/genitalia, and stomach. Sexual orientation was also found to be a relevant factor, with different patterns in sexting experiences emerging across identities. The current study adds to the mounting evidence that sexting is a normative sexual behavior. Sexual education programs should provide youth with information on consent and safe sexting practices rather than follow an abstinence approach.
Progress monitoring is integral to evidence-based practice. Correctional settings, especially the supervision of individuals who commit sexual offenses, elicit public concern; negative outcomes can ...be catastrophic. Using a prospective longitudinal study of 2,939 men with a history of sexual offenses undergoing community supervision, we examined different models of progress monitoring and how they should inform the assessment of risk for sexual recidivism. We found that the most recent assessment scores of the ACUTE-2007 and STABLE-2007 sexual recidivism risk tools provided the best information about reoffending risk compared to using (a) the worst period of adjustments (i.e., highest risk score), (b) the best period of adjustments (i.e., lowest risk score), or (c) a rolling average of scores. We also found that the latest STABLE-2007 scores incrementally predicted sexual recidivism beyond baseline risk as assessed by demographic and criminal history variables (Static-99R). We conclude that the risk for sexual recidivism changes over time and that community corrections is advanced by repeated assessment of dynamic (changeable) risk factors. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: journal abstract)
This article describes principles for developing risk category labels for criterion referenced prediction measures, and demonstrates their utility by creating new risk categories for the Static-99R ...and Static-2002R sexual offender risk assessment tools. Currently, risk assessments in corrections and forensic mental health are typically summarized in 1 of 3 words: low, moderate, or high. Although these risk labels have strong influence on decision makers, they are interpreted differently across settings, even among trained professionals. The current article provides a framework for standardizing risk communication by matching (a) the information contained in risk tools to (b) a broadly applicable classification of "riskiness" that is independent of any particular offender risk scale. We found that the new, common STATIC risk categories not only increase concordance of risk classification (from 51% to 72%)-they also allow evaluators to make the same inferences for offenders in the same category regardless of which instrument was used to assign category membership. More generally, we argue that the risk categories should be linked to the decisions at hand, and that risk communication can be improved by grounding these risk categories in evidence-based definitions.
Missing data are pervasive in risk assessment but their impact on predictive accuracy has largely been unexplored. Common techniques for handling missing risk data include summing available items or ...proration; however, multiple imputation is a more defensible approach that has not been methodically tested against these simpler techniques. We compared the validity of these three missing data techniques across six conditions using STABLE-2007 (
= 4,286) and SARA-V2 (
= 455) assessments from men on community supervision in Canada. Condition 1 was the observed data (low missingness), and Conditions 2 to 6 were generated missing data conditions, whereby 1% to 50% of items per case were randomly deleted in 10% increments. Relative predictive accuracy was unaffected by missing data, and simpler techniques performed just as well as multiple imputation, but summed totals underestimated absolute risk. The current study therefore provides empirical justification for using proration when data are missing within a sample.
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